Predicting network activity from high throughput metabolomics.
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ABSTRACT:
SUBMITTER: Li S
PROVIDER: S-EPMC3701697 | biostudies-literature | 2013
REPOSITORIES: biostudies-literature
Publications
Predicting network activity from high throughput metabolomics.
Li Shuzhao S Park Youngja Y Duraisingham Sai S Strobel Frederick H FH Khan Nooruddin N Soltow Quinlyn A QA Jones Dean P DP Pulendran Bali B
PLoS computational biology 20130704 7
The functional interpretation of high throughput metabolomics by mass spectrometry is hindered by the identification of metabolites, a tedious and challenging task. We present a set of computational algorithms which, by leveraging the collective power of metabolic pathways and networks, predict functional activity directly from spectral feature tables without a priori identification of metabolites. The algorithms were experimentally validated on the activation of innate immune cells. ...[more]
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